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6 dépôts

Awesome GitHub RepositoriesFlat-File SQL Analysis

Applying SQL queries to analyze structured text files without database imports.

Distinguishing note: Existing candidates focus on SQL scripts or performance analysis rather than analyzing raw text files using SQL

Explore 6 awesome GitHub repositories matching data & databases · Flat-File SQL Analysis. Refine with filters or upvote what's useful.

Awesome Flat-File SQL Analysis GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • dinedal/textqlAvatar de dinedal

    dinedal/textql

    9,109Voir sur GitHub↗

    TextQL is a command line SQL query engine designed to execute relational queries directly against structured text files, such as CSV and TSV, without requiring a database import. It functions as a relational text file analyzer and a CSV processor that treats plain text files as virtual tables for filtering, joining, and aggregating data. The tool is built as a pipe-compatible data transformation utility, allowing it to process data from standard input and output formatted datasets. It enables relational joins across multiple files or directories within a single query to analyze relationships

    Allows running SQL queries on CSV or TSV files to filter and aggregate data without importing it into a database.

    Go
    Voir sur GitHub↗9,109
  • google/perfettoAvatar de google

    google/perfetto

    5,558Voir sur GitHub↗

    Perfetto is a platform for system-level performance tracing and analysis on Linux and Android. It combines a high-throughput trace recorder, a SQL-based query engine, and a browser-based visualizer into a single toolchain. The platform covers CPU scheduling and call-stack profiling, native and Java heap memory allocation tracking, GPU and graphics events, and system-wide counters such as CPU frequency and power consumption. The architecture decouples trace recording from offline analysis, using a compact protobuf format for event encoding and columnar storage for efficient SQL queries. The we

    Applies SQL queries to analyze structured profiling data imported from pprof files.

    C++
    Voir sur GitHub↗5,558
  • briefercloud/brieferAvatar de briefercloud

    briefercloud/briefer

    4,308Voir sur GitHub↗

    Briefer est une plateforme de notebook de données interactif et un outil de tableau de bord de business intelligence utilisé pour l'analyse de données collaborative et le reporting. Il fournit un environnement conteneurisé pour construire des rapports qui combinent SQL, Python et Markdown avec des visualisations natives. La plateforme dispose d'un assistant de code intégré qui utilise de grands modèles de langage pour générer des snippets SQL et Python à partir de prompts en langage naturel. Elle est conçue comme une application de données Kubernetes, se déployant via des charts Helm pour gérer des environnements de calcul isolés et assurer des ressources séparées par page via une isolation basée sur des pods. Le système couvre un large éventail de capacités incluant la connectivité aux bases de données externes, la co-édition en temps réel et la livraison automatisée de rapports via la planification. Il s'intègre avec OpenID Connect pour le provisionnement d'identité et fournit un contrôle d'accès basé sur les rôles, une gestion sécurisée des identifiants et la mise en cache des requêtes basée sur les résultats. L'application est déployée et mise à l'échelle à travers des clusters Kubernetes en utilisant des charts Helm gérés.

    Allows importing local files to be analyzed using SQL queries without needing a formal database import.

    TypeScriptanalyticsbibigquery
    Voir sur GitHub↗4,308
  • hvf/franchiseAvatar de HVF

    HVF/franchise

    4,008Voir sur GitHub↗

    Franchise is a database query tool and notebook SQL client that allows users to run queries and analyze datasets. It functions as a local data processor with a browser-based engine for executing SQL commands against CSV, JSON, and XLSX files without uploading data to a remote server. The project uses a cell-based interface to organize queries and results in an interactive, document-like layout. It supports a workflow where users can fork queries into side-by-side layouts to compare different SQL variations and their results without overwriting existing code. The system provides a unified int

    Applies SQL queries to analyze structured local files like CSV, JSON, and XLSX without requiring database imports.

    JavaScriptbigquerydatabasemysql
    Voir sur GitHub↗4,008
  • multiprocessio/dsqAvatar de multiprocessio

    multiprocessio/dsq

    3,866Voir sur GitHub↗

    dsq is a command-line interface and data engine for executing SQL queries against local structured files, such as CSV, JSON, Parquet, and Excel, without requiring a formal database import. It functions as a schema-inference engine that automatically detects data types and maps heterogeneous file structures into relational tables for analysis. The tool utilizes a lazy stream data processor and checksum-based disk caching to handle large datasets with minimal memory usage. It provides a persistent interactive shell for iterative data exploration, allowing users to inspect inferred schemas and r

    Executes SQL queries against CSV, JSON, and Parquet files without importing them into a formal database engine.

    Go
    Voir sur GitHub↗3,866
  • dathere/qsvAvatar de dathere

    dathere/qsv

    3,687Voir sur GitHub↗

    qsv is a high-performance command line toolkit for querying, transforming, and analyzing comma-separated value files. It functions as a data wrangling interface and a tabular data profiler, featuring a query engine capable of executing SQL statements and joins directly on flat files without requiring a database. The project is distinguished by its ability to process massive datasets that exceed available system memory. This is achieved through disk-based external memory processing, including multithreaded merge sorting, on-disk hash tables for deduplication, and lightweight file indexing for

    Executes complex SQL queries and joins directly on flat CSV files without requiring a database engine.

    Rustaickancsv
    Voir sur GitHub↗3,687
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